A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
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Updated
Jul 5, 2024 - Python
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
A Python package to assess and improve fairness of machine learning models.
Responsible AI Toolbox is a suite of tools providing model and data exploration and assessment user interfaces and libraries that enable a better understanding of AI systems. These interfaces and libraries empower developers and stakeholders of AI systems to develop and monitor AI more responsibly, and take better data-driven actions.
🐢 Open-Source Evaluation & Testing for LLMs and ML models
Fairness Aware Machine Learning. Bias detection and mitigation for datasets and models.
Toolkit for Auditing and Mitigating Bias and Fairness of Machine Learning Systems 🔎🤖🧰
The LinkedIn Fairness Toolkit (LiFT) is a Scala/Spark library that enables the measurement of fairness in large scale machine learning workflows.
[ACL 2020] Towards Debiasing Sentence Representations
Talks & Workshops by the CODAIT team
FairPut - Machine Learning Fairness Framework with LightGBM — Explainability, Robustness, Fairness (by @firmai)
Deploy a Custom Machine Learning engine and Monitor Payload Logging and Fairness using AI OpenScale
WEFE: The Word Embeddings Fairness Evaluation Framework. WEFE is a framework that standardizes the bias measurement and mitigation in Word Embeddings models. Please feel welcome to open an issue in case you have any questions or a pull request if you want to contribute to the project!
Data and Model-based approaches for Mitigating Bias in Machine Learning Applications
A curated list of awesome academic research, books, code of ethics, data sets, institutes, newsletters, principles, podcasts, reports, tools, regulations and standards related to Responsible AI, Trustworthy AI, and Human-Centered AI.
[ICML 2021] Towards Understanding and Mitigating Social Biases in Language Models
SIREN: A Simulation Framework for Understanding the Effects of Recommender Systems in Online News Environments
Slides, videos and other potentially useful artifacts from various presentations on responsible machine learning.
This GitHub repository offers resources to create fair and unbiased AI systems, including libraries, tools and tutorials on identifying and mitigating bias in machine learning models and implementing fairness in AI.
Responsible AI Workshop: a series of tutorials & walkthroughs to illustrate how put responsible AI into practice
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